文本分类技术综述

M. M. Evangeline, K. Shyamala
{"title":"文本分类技术综述","authors":"M. M. Evangeline, K. Shyamala","doi":"10.1109/ICIPTM52218.2021.9388332","DOIUrl":null,"url":null,"abstract":"The amount of data being generated during recent times has been exponentially huge. The data mainly comprises of unstructured data in the form of textual information like emails, tweets, articles etc. To gain information from these textual data, traditional way of analyzing cannot be used. There is a need for efficient techniques for analyzing these data. Text mining is defined as the process of transforming this unstructured data into understandable and meaningful information. Text Mining is a subfield of Artificial Intelligence which aims to automatically process the data and gain insights from the huge voluminous data. In this paper, several techniques used for classifying the data have been discussed. An overview about the dimensionality reduction methodology and how it can enhance the categorization process has been highlighted. It also aims with a future research scope in extending this categorization process along with dimensionality reduction procedures.","PeriodicalId":315265,"journal":{"name":"2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"40 12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Text Categorization Techniques: A Survey\",\"authors\":\"M. M. Evangeline, K. Shyamala\",\"doi\":\"10.1109/ICIPTM52218.2021.9388332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The amount of data being generated during recent times has been exponentially huge. The data mainly comprises of unstructured data in the form of textual information like emails, tweets, articles etc. To gain information from these textual data, traditional way of analyzing cannot be used. There is a need for efficient techniques for analyzing these data. Text mining is defined as the process of transforming this unstructured data into understandable and meaningful information. Text Mining is a subfield of Artificial Intelligence which aims to automatically process the data and gain insights from the huge voluminous data. In this paper, several techniques used for classifying the data have been discussed. An overview about the dimensionality reduction methodology and how it can enhance the categorization process has been highlighted. It also aims with a future research scope in extending this categorization process along with dimensionality reduction procedures.\",\"PeriodicalId\":315265,\"journal\":{\"name\":\"2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"volume\":\"40 12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIPTM52218.2021.9388332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Innovative Practices in Technology and Management (ICIPTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIPTM52218.2021.9388332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

近年来产生的数据量呈指数级增长。数据主要由非结构化数据组成,以文本信息的形式存在,如电子邮件、tweets、文章等。要从这些文本数据中获取信息,传统的分析方法是无法使用的。需要一种有效的技术来分析这些数据。文本挖掘被定义为将非结构化数据转换为可理解且有意义的信息的过程。文本挖掘是人工智能的一个子领域,旨在对数据进行自动处理,并从海量数据中获得见解。本文讨论了几种用于数据分类的技术。概述了降维方法以及它如何增强分类过程。它还旨在与未来的研究范围,以扩大这一分类过程与降维程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text Categorization Techniques: A Survey
The amount of data being generated during recent times has been exponentially huge. The data mainly comprises of unstructured data in the form of textual information like emails, tweets, articles etc. To gain information from these textual data, traditional way of analyzing cannot be used. There is a need for efficient techniques for analyzing these data. Text mining is defined as the process of transforming this unstructured data into understandable and meaningful information. Text Mining is a subfield of Artificial Intelligence which aims to automatically process the data and gain insights from the huge voluminous data. In this paper, several techniques used for classifying the data have been discussed. An overview about the dimensionality reduction methodology and how it can enhance the categorization process has been highlighted. It also aims with a future research scope in extending this categorization process along with dimensionality reduction procedures.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信